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Explanation of INT8 ConvRot (FP8 is no longer needed)

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Why This Matters

The introduction of INT8 ConvRot marks a significant advancement in AI model quantization, offering improved performance over previous FP8 formats and potentially becoming the new standard for 8-bit models. This development benefits both consumers and the tech industry by enabling faster, more efficient AI processing, especially on GeForce RTX series GPUs. As support expands, it could lead to widespread adoption and more optimized AI applications.

Key Takeaways

The modeling and quantization method called INT8 ConvRot, which was natively supported in ComfyUI v0.27.0 released on July 1, 2026, is a hot topic.

It is particularly beneficial for the GeForce RTX 20/30 series, but it has also been reported to provide performance exceeding the previously standard FP8 and FP8 Scaled formats on the GeForce RTX 40/50 series as well.

Because of this, it is said that INT8 ConvRot will become the standard for all 8-bit quantized models, and support is actually being advanced by Comfy-Org.

Since information has not yet spread widely and many people are misunderstanding or confusing it, I will organize and explain it in this article.

2026/7/7: Added that Forge Neo now supports INT8 ConvRot

2026/7/6: Added information regarding Kimama-san's INT8 ConvRot evaluation results

2026/7/5: Added information about GGUF in "Classification of Modeling Methods and Formats"

2026/7/5: Added information about Triton and PyTorch in "How to use INT8 ConvRot"

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